library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4
## ✔ tibble 3.1.7 ✔ dplyr 1.0.9
## ✔ tidyr 1.2.0 ✔ stringr 1.4.0
## ✔ readr 2.1.2 ✔ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
data()
library(gapminder)
## Warning: package 'gapminder' was built under R version 4.2.1
ca <- read.csv("https://raw.githubusercontent.com/ScienceParkStudyGroup/r-lesson-based-on-ohi-data-training/gh-pages/data/ca.csv")
glimpse(ca)
## Rows: 789
## Columns: 7
## $ region <chr> "PW", "PW", "PW", "PW", "PW", "PW", "PW", "PW", "PW", "PW", …
## $ state <chr> "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", …
## $ code <chr> "CHIS", "CHIS", "CHIS", "CHIS", "CHIS", "CHIS", "CHIS", "CHI…
## $ park_name <chr> "Channel Islands National Park", "Channel Islands National P…
## $ type <chr> "National Park", "National Park", "National Park", "National…
## $ visitors <int> 1200, 1500, 1600, 300, 15700, 31000, 33100, 32000, 24400, 31…
## $ year <int> 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, …
ggplot(ca,aes(x=year,y= visitors,color=park_name))+
geom_point(alpha=.5)+
labs(x="Year", y="Visitors", title= "National Park Visitors")+
theme(
legend.title = element_blank()
)
ggplot(ca,aes(x=year,y= visitors,colour=park_name))+
geom_point(alpha=.5)+
facet_wrap(~code, scales = "free")+
theme_bw()
ggplot(ca,aes(x=year,y= visitors,colour=state))+
geom_point(alpha=.5)+
labs(x="Year", y="Visitors", title= "Southeast States National Park Visitation")
theme_light()
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library(tidyverse)
library(gapminder)
data <- gapminder
glimpse(data)
## Rows: 1,704
## Columns: 6
## $ country <fct> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", …
## $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
## $ year <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, …
## $ lifeExp <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.8…
## $ pop <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 12…
## $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134, …
ggplot(data , aes(x= log(gdpPercap), col= year, y= lifeExp , size=pop))+
geom_jitter()+
facet_wrap(~continent, scale="free")
Ex <- read.csv("https://raw.githubusercontent.com/ScienceParkStudyGroup/r-lesson-based-on-ohi-data-training/gh-pages/data/se.csv")
glimpse(Ex)
## Rows: 453
## Columns: 7
## $ region <chr> "SE", "SE", "SE", "SE", "SE", "SE", "SE", "SE", "SE", "SE", …
## $ state <chr> "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", …
## $ code <chr> "BISC", "BISC", "BISC", "BISC", "BISC", "BISC", "BISC", "BIS…
## $ park_name <chr> "Biscayne National Park", "Biscayne National Park", "Biscayn…
## $ type <chr> "National Park", "National Park", "National Park", "National…
## $ visitors <int> 78147, 243100, 409700, 351500, 339100, 205900, 177416, 20293…
## $ year <int> 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, …
ggplot(Ex, aes(x=park_name, y=visitors, col= park_name))+
geom_boxplot()+
geom_jitter(alpha=0.3)+
coord_flip()+
theme_bw()
### interactive charts
library(plotly)
## Warning: package 'plotly' was built under R version 4.2.1
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
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## layout
Analysis <- ggplot(Ex, aes(x=park_name, y=visitors, col= park_name))+
geom_boxplot()+
geom_jitter(alpha=0.3)+
coord_flip()+
theme_bw()
ggplotly()